{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ec8d01ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "device_target: Ascend\n",
      "dataset_sink_mode: True\n",
      "训练集路径：data/10-batches-bin\n",
      "测试集路径：data/10-verify-bin\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(125.306918046875, 122.950394140625, 113.86538318359375)\n",
      "(62.9932192777234, 62.08870764035836, 66.7048996406375)\n",
      "acc_eval:  0.2616\n",
      "epoch time: 15085.093 ms, per step time: 9.658 ms\n",
      "acc_eval:  0.4589\n",
      "epoch time: 3776.843 ms, per step time: 2.418 ms\n",
      "acc_eval:  0.5251\n",
      "epoch time: 3997.071 ms, per step time: 2.559 ms\n",
      "acc_eval:  0.5458\n",
      "epoch time: 4067.235 ms, per step time: 2.604 ms\n",
      "acc_eval:  0.5815\n",
      "epoch time: 3950.105 ms, per step time: 2.529 ms\n",
      "acc_eval:  0.5798\n",
      "epoch time: 4133.584 ms, per step time: 2.646 ms\n",
      "acc_eval:  0.5763\n",
      "epoch time: 4329.091 ms, per step time: 2.772 ms\n",
      "acc_eval:  0.5967\n",
      "epoch time: 3853.651 ms, per step time: 2.467 ms\n",
      "acc_eval:  0.5766\n",
      "epoch time: 3859.703 ms, per step time: 2.471 ms\n",
      "acc_eval:  0.5872\n",
      "epoch time: 3028.161 ms, per step time: 1.939 ms\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'accuracy': 0.5967, 'loss': 1.1671301010251045}\n",
      "acc_eval:  0.4926\n",
      "epoch time: 28894.568 ms, per step time: 18.498 ms\n",
      "acc_eval:  0.5739\n",
      "epoch time: 4111.717 ms, per step time: 2.632 ms\n",
      "acc_eval:  0.6439\n",
      "epoch time: 4210.887 ms, per step time: 2.696 ms\n",
      "acc_eval:  0.6793\n",
      "epoch time: 4078.096 ms, per step time: 2.611 ms\n",
      "acc_eval:  0.6937\n",
      "epoch time: 4106.370 ms, per step time: 2.629 ms\n",
      "acc_eval:  0.6971\n",
      "epoch time: 4097.228 ms, per step time: 2.623 ms\n",
      "acc_eval:  0.7184\n",
      "epoch time: 3730.102 ms, per step time: 2.388 ms\n",
      "acc_eval:  0.7116\n",
      "epoch time: 3920.163 ms, per step time: 2.510 ms\n",
      "acc_eval:  0.7308\n",
      "epoch time: 3877.172 ms, per step time: 2.482 ms\n",
      "acc_eval:  0.7322\n",
      "epoch time: 3296.090 ms, per step time: 2.110 ms\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'accuracy': 0.7322, 'loss': 0.7810303118824958}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import mindspore\n",
    "\n",
    "# mindspore.dataset\n",
    "import mindspore.dataset as ds # 数据集的载入\n",
    "import mindspore.dataset.transforms.c_transforms as C # 常用转化算子\n",
    "import mindspore.dataset.vision.c_transforms as CV # 图像转化算子\n",
    "\n",
    "# mindspore.common\n",
    "from mindspore.common import dtype as mstype # 数据形态转换\n",
    "from mindspore.common.initializer import Normal # 参数初始化\n",
    "\n",
    "# mindspore.nn\n",
    "import mindspore.nn as nn # 各类网络层都在nn里面\n",
    "from mindspore.nn.metrics import Accuracy, Loss # 测试模型用\n",
    "\n",
    "# mindspore.train.callback\n",
    "from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor, Callback # 回调函数\n",
    "\n",
    "\n",
    "from mindspore import Model # 承载网络结构\n",
    "from mindspore import save_checkpoint, load_checkpoint # 保存与读取最佳参数\n",
    "from mindspore import context # 设置mindspore运行的环境\n",
    "\n",
    "\n",
    "import numpy as np # numpy\n",
    "import matplotlib.pyplot as plt # 可视化用\n",
    "import copy # 保存网络参数用\n",
    "\n",
    "# 数据路径处理\n",
    "import os, stat  \n",
    "\n",
    "device_target = context.get_context('device_target') \n",
    "# 获取运行装置（CPU，GPU，Ascend）\n",
    "dataset_sink_mode = True if device_target in ['Ascend','GPU'] else False \n",
    "# 是否将数据通过pipeline下发到装置上\n",
    "context.set_context(mode = context.GRAPH_MODE, device_target = device_target) \n",
    "# 设置运行环境，静态图context.GRAPH_MODE指向静态图模型，即在运行之前会把全部图建立编译完毕\n",
    "\n",
    "print(f'device_target: {device_target}')\n",
    "print(f'dataset_sink_mode: {dataset_sink_mode}') \n",
    "\n",
    "# 数据路径\n",
    "train_path = os.path.join('data','10-batches-bin') # 训练集路径\n",
    "test_path = os.path.join('data','10-verify-bin') #请填写测试集路径\n",
    "print(f'训练集路径：{train_path}')\n",
    "print(f'测试集路径：{test_path}') \n",
    "\n",
    "# 创建图像标签列表\n",
    "category_dict = {0:'airplane',1:'automobile',2:'bird',3:'cat',4:'deer',5:'dog',\n",
    "                 6:'frog',7:'horse',8:'ship',9:'truck'}# 请补充图片的类别\n",
    "\n",
    "# 载入展示用数据\n",
    "demo_data = ds.Cifar10Dataset(test_path)\n",
    "\n",
    "# 设置图像大小\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "# 打印9张子图\n",
    "i = 1\n",
    "for dic in demo_data.create_dict_iterator():\n",
    "    plt.subplot(3,3,i)\n",
    "    plt.imshow(dic['image'].asnumpy()) # asnumpy：将 MindSpore tensor 转换成 numpy\n",
    "    plt.axis('off')\n",
    "    plt.title(category_dict[dic['label'].asnumpy().item()])\n",
    "    i +=1\n",
    "    if i > 9 :\n",
    "        break\n",
    "\n",
    "plt.show() \n",
    "\n",
    "ds_train = ds.Cifar10Dataset(train_path)\n",
    "#计算数据集平均数和标准差，数据标准化时使用\n",
    "tmp = np.asarray( [x['image'] for x in ds_train.create_dict_iterator(output_numpy=True)] )\n",
    "RGB_mean = tuple(np.mean(tmp, axis=(0, 1, 2)))\n",
    "RGB_std = tuple(np.std(tmp, axis=(0, 1, 2))) #请补充np函数以计算标准差\n",
    "\n",
    "print(RGB_mean)\n",
    "print(RGB_std) \n",
    "\n",
    "def create_dataset(data_path, batch_size = 32, repeat_num=1, usage = 'train'):\n",
    "    \"\"\" \n",
    "    数据处理\n",
    "    \n",
    "    Args:\n",
    "        data_path (str): 数据路径\n",
    "        batch_size (int): 批量大小\n",
    "        usage (str): 训练或测试\n",
    "        \n",
    "    Returns:\n",
    "        Dataset对象\n",
    "    \"\"\"\n",
    "    \n",
    "    # 载入数据集\n",
    "    data = ds.Cifar10Dataset(data_path)\n",
    "    \n",
    "    # 打乱数据集\n",
    "    data = data.shuffle(buffer_size=10000)\n",
    "    \n",
    "    # 定义算子\n",
    "    if usage=='train':\n",
    "        trans = [\n",
    "            CV.Normalize(RGB_mean, RGB_std), # 数据标准化\n",
    "\n",
    "            # 数据增强\n",
    "            CV.RandomCrop([32, 32], [4, 4, 4, 4]), # 随机裁剪\n",
    "            CV.RandomHorizontalFlip(), # 随机翻转\n",
    "\n",
    "            CV.HWC2CHW() # 通道前移（为配适网络，CHW的格式可最佳发挥昇腾芯片算力）\n",
    "        ]\n",
    "    else:\n",
    "        trans = [\n",
    "            CV.Normalize(RGB_mean, RGB_std), # 数据标准化\n",
    "            CV.HWC2CHW() # 通道前移（为配适网络，CHW的格式可最佳发挥昇腾芯片算力）\n",
    "        ]\n",
    "    \n",
    "    typecast_op = C.TypeCast(mstype.int32) # 原始数据的标签是unint，计算损失需要int\n",
    "\n",
    "    # 算子运算\n",
    "    data = data.map(input_columns='label', operations=typecast_op)\n",
    "    data = data.map(input_columns='image', operations=trans)\n",
    "    \n",
    "    # 批处理\n",
    "    data = data.batch(batch_size, drop_remainder=True)\n",
    "    \n",
    "    # 重复\n",
    "    data = data.repeat(repeat_num)\n",
    "    \n",
    "    return data \n",
    "\n",
    "\n",
    "class LeNet5(nn.Cell):\n",
    "    \"\"\"\n",
    "    LeNet5网络\n",
    "\n",
    "    Args:\n",
    "        num_class (int): 输出分类数\n",
    "        num_channel (int): 输入通道数\n",
    "    Returns:\n",
    "        Tensor, 输出张量\n",
    "\n",
    "    Examples:\n",
    "        >>> LeNet5(10, 3)\n",
    "    \"\"\"\n",
    "    \n",
    "    # 定义算子\n",
    "    def __init__(self, num_class=10, num_channel=3):\n",
    "        super(LeNet5, self).__init__()\n",
    "        # 卷积层\n",
    "        self.conv1 = nn.Conv2d(num_channel, 6, 5, pad_mode='valid')\n",
    "        self.conv2 = nn.Conv2d(6, 16, 5, pad_mode='valid')\n",
    "        \n",
    "        # 全连接层\n",
    "        self.fc1 = nn.Dense(16 * 5 * 5, 120, weight_init=Normal(0.02))\n",
    "        self.fc2 = nn.Dense(120, 84, weight_init=Normal(0.02))\n",
    "        self.fc3 = nn.Dense(84, num_class, weight_init=Normal(0.02))\n",
    "        \n",
    "        # 激活函数\n",
    "        self.relu = nn.ReLU()\n",
    "        \n",
    "        # 最大池化成\n",
    "        self.max_pool2d = nn.MaxPool2d(kernel_size=2, stride=2)\n",
    "        \n",
    "        # 网络展开\n",
    "        self.flatten = nn.Flatten()\n",
    "\n",
    "# 建构网络\n",
    "# 请根据Lenet网络结构，构建如下模型，请留意，卷积层后需要加激活函数\n",
    "    def construct(self, x):\n",
    "        x = self.conv1(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.max_pool2d(x)\n",
    "        x = self.conv2(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.max_pool2d(x)\n",
    "        x = self.flatten(x)\n",
    "        x = self.fc1(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.fc2(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.fc3(x)\n",
    "        return x \n",
    "    \n",
    "train_data = create_dataset(train_path, batch_size = 32, usage = 'train') # 训练数据集\n",
    "test_data = create_dataset(test_path, batch_size = 50, usage= 'test') # 测试数据集\n",
    "\n",
    "# 网络\n",
    "network1 = LeNet5(10)\n",
    "\n",
    "# 损失函数\n",
    "net_loss = nn.SoftmaxCrossEntropyWithLogits(sparse=True, reduction='mean')\n",
    "\n",
    "# 优化器\n",
    "net_opt = nn.Momentum(params=network1.trainable_params(), learning_rate=0.01, momentum=0.9)\n",
    "\n",
    "# 模型，请补充模型的超参数\n",
    "model = Model(network = network1, loss_fn=net_loss, optimizer=net_opt, metrics={'accuracy': Accuracy(), 'loss':Loss()}) \n",
    "\n",
    "# 记录模型每个epoch的loss\n",
    "class TrainHistroy(Callback):\n",
    "    \"\"\"\n",
    "    记录模型训练时每个epoch的loss的回调函数\n",
    "\n",
    "    Args:\n",
    "        history (list): 传入list以保存模型每个epoch的loss\n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, history):\n",
    "        super(TrainHistroy, self).__init__()\n",
    "        self.history = history\n",
    "        \n",
    "    # 每个epoch结束时执行\n",
    "    def epoch_end(self, run_context):\n",
    "        cb_params = run_context.original_args()\n",
    "        loss = cb_params.net_outputs.asnumpy()\n",
    "        self.history.append(loss)\n",
    "        \n",
    "\n",
    "# 测试并记录模型在测试集的loss和accuracy，每个epoch结束时进行模型测试并记录结果，跟踪并保存准确率最高的模型网络参数\n",
    "class EvalHistory(Callback):\n",
    "    \"\"\"\n",
    "    记录模型训练时每个epoch在测试集的loss和accuracy的回调函数，并保存准确率最高的模型网络参数\n",
    "\n",
    "    Args:\n",
    "        model (Cell): 模型，评估loss和accuracy用\n",
    "        loss_history (list): 传入list以保存模型每个epoch在测试集的loss\n",
    "        acc_history (list): 传入list以保存模型每个epoch在测试集的accuracy\n",
    "        eval_data (Dataset): 测试集，评估模型loss和accuracy用\n",
    "    \"\"\"\n",
    "    \n",
    "    #保存accuracy最高的网络参数\n",
    "    best_param = None\n",
    "    \n",
    "    def __init__(self, model, loss_history, acc_history, eval_data):\n",
    "        super(EvalHistory, self).__init__()\n",
    "        self.loss_history = loss_history\n",
    "        self.acc_history = acc_history\n",
    "        self.eval_data = eval_data\n",
    "        self.model = model\n",
    "    \n",
    "    # 每个epoch结束时执行\n",
    "    def epoch_end(self, run_context):\n",
    "        cb_params = run_context.original_args()\n",
    "        res = self.model.eval(self.eval_data, dataset_sink_mode=False)\n",
    "        \n",
    "        if len(self.acc_history)==0 or res['accuracy']>=max(self.acc_history):\n",
    "            self.best_param = copy.deepcopy(cb_params.network)\n",
    "            \n",
    "        self.loss_history.append(res['loss'])\n",
    "        self.acc_history.append(res['accuracy'])\n",
    "        \n",
    "        print('acc_eval: ',res['accuracy'])\n",
    "    \n",
    "    # 训练结束后执行\n",
    "    def end(self, run_context):\n",
    "        # 保存最优网络参数\n",
    "        best_param_path = os.path.join(ckpt_path, 'best_param.ckpt')\n",
    "        \n",
    "        if os.path.exists(best_param_path):\n",
    "            # best_param.ckpt已存在时MindSpore会覆盖旧的文件，这里修改文件读写权限防止报错\n",
    "            os.chmod(best_param_path, stat.S_IWRITE)\n",
    "            \n",
    "        save_checkpoint(self.best_param, best_param_path) \n",
    "        \n",
    "        \n",
    "ckpt_path = os.path.join('.','results') # 网络参数保存路径\n",
    "hist = {'loss':[], 'loss_eval':[], 'acc_eval':[]} # 训练过程记录\n",
    "\n",
    "# 网络参数自动保存，这里设定每2000个step保存一次，最多保存10次\n",
    "config_ck = CheckpointConfig(save_checkpoint_steps=2000,\n",
    "                             keep_checkpoint_max=10)\n",
    "ckpoint_cb = ModelCheckpoint(prefix='checkpoint_lenet', directory=ckpt_path, config=config_ck)\n",
    "\n",
    "# 监控每次迭代的时间\n",
    "time_cb = TimeMonitor(data_size=ds_train.get_dataset_size())\n",
    "\n",
    "# 监控loss值\n",
    "loss_cb = LossMonitor(per_print_times=500)\n",
    "\n",
    "# 记录每次迭代的模型损失值\n",
    "train_hist_cb = TrainHistroy(hist['loss'])\n",
    "\n",
    "# 测试并记录模型在验证集的loss和accuracy，并保存最优网络参数\n",
    "eval_hist_cb = EvalHistory(model = model,\n",
    "                           loss_history = hist['loss_eval'], \n",
    "                           acc_history = hist['acc_eval'], \n",
    "                           eval_data = test_data) \n",
    "\n",
    "epoch = 10 # 迭代次数\n",
    "# 开始训练\n",
    "model.train(epoch, train_data, callbacks=[train_hist_cb, eval_hist_cb, time_cb, ckpoint_cb, loss_cb], dataset_sink_mode=dataset_sink_mode)\n",
    "\n",
    "# 定义loss记录绘制函数\n",
    "def plot_loss(hist):\n",
    "    plt.plot(hist['loss'], marker='.')\n",
    "    plt.plot(hist['loss_eval'], marker='.')\n",
    "    plt.title('loss record')\n",
    "    plt.xlabel('epoch')\n",
    "    plt.ylabel('loss')\n",
    "    plt.grid()\n",
    "    plt.legend(['loss_train', 'loss_eval'], loc='upper right')\n",
    "    plt.show()\n",
    "    plt.close()\n",
    "\n",
    "plot_loss(hist) \n",
    "\n",
    "def plot_accuracy(hist):\n",
    "    plt.plot(hist['acc_eval'], marker='.')\n",
    "    plt.title('accuracy history')\n",
    "    plt.xlabel('epoch')\n",
    "    plt.ylabel('acc_eval')\n",
    "    plt.grid()\n",
    "    plt.show()\n",
    "    plt.close()\n",
    "\n",
    "plot_accuracy(hist)\n",
    "\n",
    "# 使用准确率最高的参数组合建立模型，并测试其在验证集上的效果\n",
    "load_checkpoint(os.path.join(ckpt_path, 'best_param.ckpt'), net=network1)\n",
    "res = model.eval(test_data, dataset_sink_mode=dataset_sink_mode)\n",
    "print(res) \n",
    "\n",
    "\n",
    "class LeNet5_2(nn.Cell):\n",
    "    \n",
    "    # 定义算子\n",
    "    def __init__(self, num_class=10, num_channel=3):\n",
    "        super(LeNet5_2, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(num_channel, 32, 3, pad_mode='valid', weight_init=Normal(0.02))\n",
    "        self.conv2 = nn.Conv2d(32, 64, 3, pad_mode='valid', weight_init=Normal(0.02))\n",
    "        self.conv3 = nn.Conv2d(64, 128, 3, pad_mode='valid', weight_init=Normal(0.02))\n",
    "        self.fc1 = nn.Dense(128*2*2, 120, weight_init=Normal(0.02))\n",
    "        self.fc2 = nn.Dense(120, 84, weight_init=Normal(0.02))\n",
    "        self.fc3 = nn.Dense(84, num_class, weight_init=Normal(0.02))\n",
    "        self.relu = nn.ReLU()\n",
    "        self.max_pool2d = nn.MaxPool2d(kernel_size=2, stride=2)\n",
    "        self.flatten = nn.Flatten()\n",
    "        self.num_class = num_class\n",
    "    \n",
    "    # 构建网络\n",
    "    def construct(self, x):\n",
    "        x = self.conv1(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.max_pool2d(x)\n",
    "        x = self.conv2(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.max_pool2d(x)\n",
    "        x = self.conv3(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.max_pool2d(x)\n",
    "        x = self.flatten(x)\n",
    "        x = self.fc1(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.fc2(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.fc3(x)\n",
    "        return x \n",
    "    \n",
    "# 如果已将数据通过pipeline下发到装置上，使用新的model需要重新载入数据\n",
    "if dataset_sink_mode:\n",
    "    # 训练数据集预处理\n",
    "    train_data = create_dataset(train_path, batch_size = 32, usage = 'train')\n",
    "    # 测试数据集预处理\n",
    "    test_data = create_dataset(test_path, batch_size = 50, usage = 'test') \n",
    "    \n",
    "# 网络\n",
    "network2 = LeNet5_2(10)\n",
    "\n",
    "# 损失函数\n",
    "net_loss = nn.SoftmaxCrossEntropyWithLogits(sparse=True, reduction='mean')\n",
    "\n",
    "# 优化器\n",
    "net_opt = nn.Adam(params=network2.trainable_params())\n",
    "\n",
    "# 模型，请补充model的超参数\n",
    "model = Model(network = network2, loss_fn=net_loss, optimizer=net_opt, metrics={'accuracy': Accuracy(), 'loss':Loss()}) \n",
    "\n",
    "hist = {'loss':[], 'loss_eval':[], 'acc_eval':[]} # 训练过程记录\n",
    "\n",
    "# 网络参数自动保存，这里设定每2000个step保存一次，最多保存10次\n",
    "config_ck = CheckpointConfig(save_checkpoint_steps=2000, keep_checkpoint_max=10)\n",
    "ckpoint_cb = ModelCheckpoint(prefix='checkpoint_lenet_2', directory=ckpt_path, config=config_ck)\n",
    "\n",
    "# 记录每次迭代的模型准确率\n",
    "train_hist_cb = TrainHistroy(hist['loss'])\n",
    "\n",
    "# 测试并记录模型在验证集的loss和accuracy，并保存最优网络参数\n",
    "eval_hist_cb = EvalHistory(model = model,\n",
    "                           loss_history = hist['loss_eval'], \n",
    "                           acc_history = hist['acc_eval'], \n",
    "                           eval_data = test_data)\n",
    "\n",
    "epoch = 10 # 迭代次数\n",
    "# 开始训练\n",
    "model.train(epoch, train_data, \n",
    "            callbacks=[train_hist_cb, eval_hist_cb, time_cb, ckpoint_cb, LossMonitor(per_print_times=500)], \n",
    "            dataset_sink_mode=dataset_sink_mode) \n",
    "\n",
    "plot_loss(hist) \n",
    "plot_accuracy(hist) \n",
    "\n",
    "# 使用准确率最高的参数组合建立模型，并测试其在验证集上的效果\n",
    "best_param = mindspore.load_checkpoint(os.path.join(ckpt_path, 'best_param.ckpt'), net=network2)\n",
    "res = model.eval(test_data, dataset_sink_mode=dataset_sink_mode)\n",
    "print(res) \n",
    "\n",
    "\n",
    "#创建图像标签列表\n",
    "category_dict = {0:'airplane',1:'automobile',2:'bird',3:'cat',4:'deer',5:'dog',\n",
    "                 6:'frog',7:'horse',8:'ship',9:'truck'}\n",
    "\n",
    "data_path=os.path.join('data', '10-verify-bin')\n",
    "\n",
    "demo_data = create_dataset(test_path, batch_size=1, usage='test')\n",
    "\n",
    "# 将数据标准化至0~1区间\n",
    "def normalize(data):\n",
    "    _range = np.max(data) - np.min(data)\n",
    "    return (data - np.min(data)) / _range\n",
    "\n",
    "# 设置图像大小\n",
    "plt.figure(figsize=(10,10))\n",
    "i = 1\n",
    "# 打印9张子图\n",
    "for dic in demo_data.create_dict_iterator():\n",
    "    # 预测单张图片\n",
    "    input_img = dic['image']\n",
    "    output = model.predict(input_img)\n",
    "    predict = np.argmax(output.asnumpy(),axis=1)[0] # 反馈可能性最大的类别\n",
    "    \n",
    "    # 可视化\n",
    "    plt.subplot(3,3,i)\n",
    "    input_image = np.squeeze(input_img.asnumpy(),axis=0) # 删除batch维度，方便可视化\n",
    "    input_image = input_image.transpose(1,2,0) # CHW转HWC，方便可视化\n",
    "    input_image = normalize(input_image) # 重新标准化，方便可视化\n",
    "    plt.imshow(input_image)\n",
    "    plt.axis('off')\n",
    "    plt.title('True: %s\\n Predict: %s'%(category_dict[dic['label'].asnumpy().item()],category_dict[predict]))\n",
    "    i +=1\n",
    "    if i > 9 :\n",
    "        break\n",
    "\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34b56ebc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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